---
title: "Who cites BERT: Pre-training of Deep Bidirectional…"
description: "23,422 papers of the Elamur Research library cite «BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding», found in their…"
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# Who cites «BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding»

23,422 papers of our library cite it (of the 140,884 whose bibliographies we read) · 1500 with a page here, the most cited first · page 4 of 15 · 301–400 · [← the paper](https://md.research.elamur.ai/free/en/papers/devlin-2019-bert-pre-training-deep-bidirectional/)

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301. [**FinGPT: Open-Source Financial Large Language Models**Hongyang Yang, Xiao-Yang Liu, Christina Dan Wang*2023 · 445 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-fingpt-open-source-financial-large/)
302. [**How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models**Phillip Rust, Jonas Pfeiffer, Ivan Vulić, et al.*2021 · 444 citations*](https://md.research.elamur.ai/free/en/papers/rust-2021-how-good-is-your-tokenizer/)
303. [**Masked Language Model Scoring**Julian Salazar, Davis Liang, Toan Q. Nguyen, et al.*2020 · 444 citations*](https://md.research.elamur.ai/free/en/papers/salazar-2020-masked-language-model-scoring/)
304. [**Ranking Generated Summaries by Correctness: An Interesting but Challenging Application for Natural Language Inference**Tobias Falke, Leonardo F. R. Ribeiro, Prasetya Ajie Utama, et al.*2019 · 444 citations*](https://md.research.elamur.ai/free/en/papers/falke-2019-ranking-generated-summaries-correctness-interesting/)
305. [**FreeLB: Enhanced Adversarial Training for Natural Language Understanding**Chen Zhu, Yu Cheng, Zhe Gan, et al.*2019 · 443 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2019-freelb-enhanced-adversarial-training-natural/)
306. [**The Faiss library**Matthijs Douze, Alexandr Guzhva, Chengqi Deng, et al.*2024 · 442 citations*](https://md.research.elamur.ai/free/en/papers/douze-2024-faiss-library/)
307. [**Pretrained Transformers Improve Out-of-Distribution Robustness**Dan Hendrycks, Xiaoyuan Liu, Eric Wallace, et al.*2020 · 442 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2020-pretrained-transformers-improve-out-distribution/)
308. [**MVBench: A Comprehensive Multi-modal Video Understanding Benchmark**Kunchang Li, Yali Wang, Yinan He, et al.*2023 · 441 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-mvbench-comprehensive-multi-modal-video/)
309. [**ShareGPT4V: Improving Large Multi-Modal Models with Better Captions**Lin Chen, Jinsong Li, Xiaoyi Dong, et al.*2023 · 441 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-sharegpt4v-improving-large-multi-modal/)
310. [**Entity-Relation Extraction as Multi-Turn Question Answering**Xiaoya Li, Fan Yin, Zijun Sun, et al.*2019 · 437 citations*](https://md.research.elamur.ai/free/en/papers/li-2019-entity-relation-extraction-as-multi/)
311. [**GPT-NER: Named Entity Recognition via Large Language Models**Shuhe Wang, Xiaofei Sun, Xiaoya Li, et al.*2025 · 436 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-gpt-ner-named-entity-recognition/)
312. [**The Falcon Series of Open Language Models**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 436 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/)
313. [**Improving Text Embeddings with Large Language Models**Liang Wang, Nan Yang, Xiaolong Huang, et al.*2024 · 433 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-improving-text-embeddings-large-language/)
314. [**Self-Alignment Pretraining for Biomedical Entity Representations**Fangyu Liu, Ehsan Shareghi, Zaiqiao Meng, et al.*2021 · 432 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-self-alignment-pretraining-biomedical-entity/)
315. [**oLMpics — On what Language Model Pre-training Captures**Alon Talmor, Yanai Elazar, Yoav Goldberg, et al.*2019 · 432 citations*](https://md.research.elamur.ai/free/en/papers/talmor-2019-olmpics-language-model-pre-training/)
316. [**Negated and Misprimed Probes for Pretrained Language Models: Birds Can Talk, But Cannot Fly**Nora Kassner, Hinrich Schütze*2020 · 431 citations*](https://md.research.elamur.ai/free/en/papers/kassner-2020-negated-misprimed-probes-pretrained-language/)
317. [**Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection**Shilong Liu, Zhaoyang Zeng, Tianhe Ren, et al.*2023 · 430 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-grounding-dino-marrying-dino-grounded/)
318. [**Analyzing the Structure of Attention in a Transformer Language Model**Jesse Vig, Yonatan Belinkov*2019 · 430 citations*](https://md.research.elamur.ai/free/en/papers/vig-2019-analyzing-structure-attention-transformer-language/)
319. [**Experience Grounds Language**Yonatan Bisk, Ari Holtzman, Jesse Thomason, et al.*2020 · 429 citations*](https://md.research.elamur.ai/free/en/papers/bisk-2020-experience-grounds-language/)
320. [**C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models**Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu, et al.*2023 · 427 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-c-eval-multi-level-multi/)
321. [**Benchmarking Retrieval-Augmented Generation for Medicine**Guangzhi Xiong, Qiao Jin, Zhiyong Lu, et al.*2024 · 426 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2024-benchmarking-retrieval-augmented-generation-medicine/)
322. [**Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling**Sebastian Hofstatter, Sheng-Chieh Lin, Jheng-Hong Yang, et al.*2021 · 425 citations*](https://md.research.elamur.ai/free/en/papers/hofstatter-2021-efficiently-teaching-effective-dense-retriever/)
323. [**Security and Privacy Challenges of Large Language Models: A Survey**Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu*2024 · 422 citations*](https://md.research.elamur.ai/free/en/papers/das-2024-security-privacy-challenges-large-language/)
324. [**Diffusion-LM Improves Controllable Text Generation**Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, et al.*2022 · 421 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-diffusion-lm-improves-controllable-text/)
325. [**Ethical and social risks of harm from Language Models**Laura Weidinger, John Mellor, Maribeth Rauh, et al.*2021 · 421 citations*](https://md.research.elamur.ai/free/en/papers/weidinger-2021-ethical-social-risks-harm-language/)
326. [**Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents**Wenlong Huang, Pieter Abbeel, Deepak Pathak, et al.*2022 · 420 citations*](https://md.research.elamur.ai/free/en/papers/huang-2022-language-models-zero-shot-planners/)
327. [**Template-Based Named Entity Recognition Using BART**Leyang Cui, Yu Wu, Jian Liu, et al.*2021 · 420 citations*](https://md.research.elamur.ai/free/en/papers/cui-2021-template-based-named-entity-recognition/)
328. [**Event Extraction as Machine Reading Comprehension**Jian Liu, Yubo Chen, Kang Liu, et al.*2020 · 420 citations*](https://md.research.elamur.ai/free/en/papers/liu-2020-event-extraction-as-machine-reading/)
329. [**ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning**Viet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh, et al.*2023 · 418 citations*](https://md.research.elamur.ai/free/en/papers/lai-2023-chatgpt-beyond-english-comprehensive-evaluation/)
330. [**Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics**Artidoro Pagnoni, Vidhisha Balachandran, Yulia Tsvetkov*2021 · 417 citations*](https://md.research.elamur.ai/free/en/papers/pagnoni-2021-understanding-factuality-abstractive-summarization-frank/)
331. [**75 Languages, 1 Model: Parsing Universal Dependencies Universally**Dan Kondratyuk, Milan Straka*2019 · 415 citations*](https://md.research.elamur.ai/free/en/papers/kondratyuk-2019-75-languages-1-model-parsing/)
332. [**Weight Poisoning Attacks on Pretrained Models**Keita Kurita, Paul Michel, Graham Neubig*2020 · 414 citations*](https://md.research.elamur.ai/free/en/papers/kurita-2020-weight-poisoning-attacks-pretrained-models/)
333. [**Are Sixteen Heads Really Better than One?**Paul Michel, Omer Levy, Graham Neubig*2019 · 412 citations*](https://md.research.elamur.ai/free/en/papers/michel-2019-sixteen-heads-really-better-than/)
334. [**Factual Probing Is MASK: Learning vs. Learning to Recall**Zexuan Zhong, Dan Friedman, Danqi Chen*2021 · 411 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2021-factual-probing-is-mask-learning/)
335. [**mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality**Qinghao Ye, Haiyang Xu, Guohai Xu, et al.*2023 · 410 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-mplug-owl-modularization-empowers-large/)
336. [**InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks**Zhe Chen, Jiannan Wu, Wenhai Wang, et al.*2023 · 409 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-internvl-scaling-up-vision/)
337. [**KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social Media**Ali Safaya, Moutasem Abdullatif, Deniz Yuret*2020 · 409 citations*](https://md.research.elamur.ai/free/en/papers/safaya-2020-kuisail-semeval-2020-task-12/)
338. [**A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Support**Ashish Sharma, Adam Miner, David Atkins, et al.*2020 · 408 citations*](https://md.research.elamur.ai/free/en/papers/sharma-2020-computational-approach-understanding-empathy-expressed/)
339. [**BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains**Yanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.*2024 · 406 citations*](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/)
340. [**Automatic Detection of Generated Text is Easiest when Humans are Fooled**Daphne Ippolito, Daniel Duckworth, Chris Callison-Burch, et al.*2019 · 406 citations*](https://md.research.elamur.ai/free/en/papers/ippolito-2019-automatic-detection-generated-text-easiest/)
341. [**Training data-efficient image transformers & distillation through attention**Hugo Touvron, Matthieu Cord, Matthijs Douze, et al.*2020 · 405 citations*](https://md.research.elamur.ai/free/en/papers/touvron-2020-training-data-efficient-image-transformers/)
342. [**AgentBench: Evaluating LLMs as Agents**Xiao Liu, Hao Yu, Hanchen Zhang, et al.*2023 · 404 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-agentbench-evaluating-llms-agents/)
343. [**Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answering**Shamane Siriwardhana, Rivindu Weerasekera, Elliott Wen, et al.*2023 · 403 citations*](https://md.research.elamur.ai/free/en/papers/siriwardhana-2023-improving-domain-adaptation-retrieval-augmented/)
344. [**True Few-Shot Learning with Language Models**Ethan Perez, Douwe Kiela, Kyunghyun Cho*2021 · 403 citations*](https://md.research.elamur.ai/free/en/papers/perez-2021-true-few-shot-learning-language/)
345. [**The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes**Douwe Kiela, Hamed Firooz, Aravind Mohan, et al.*2020 · 403 citations*](https://md.research.elamur.ai/free/en/papers/kiela-2020-hateful-memes-challenge-detecting-hate/)
346. [**Social Biases in NLP Models as Barriers for Persons with Disabilities**Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, et al.*2020 · 402 citations*](https://md.research.elamur.ai/free/en/papers/hutchinson-2020-social-biases-nlp-models-as/)
347. [**Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning**Mitchell Gordon, Kevin Duh, Nicholas Andrews*2020 · 400 citations*](https://md.research.elamur.ai/free/en/papers/gordon-2020-compressing-bert-studying-effects-weight/)
348. [**How to Fine-Tune BERT for Text Classification?**Chi Sun, Xipeng Qiu, Yige Xu, et al.*2019 · 400 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-fine-tune-bert-text-classification/)
349. [**Neural Architectures for Nested NER through Linearization**Jana Straková, Milan Straka, Jan Hajic*2019 · 400 citations*](https://md.research.elamur.ai/free/en/papers/strakova-2019-neural-architectures-nested-ner-through/)
350. [**A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios**Michael A. Hedderich, Lukas Lange, Heike Adel, et al.*2021 · 399 citations*](https://md.research.elamur.ai/free/en/papers/hedderich-2021-survey-recent-approaches-natural-language/)
351. [**LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models**Zhiqiang Hu, Lei Wang, Yihuai Lan, et al.*2023 · 398 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-llm-adapters-adapter-family-parameter/)
352. [**LongT5: Efficient Text-To-Text Transformer for Long Sequences**Mandy Guo, Joshua Ainslie, David Uthus, et al.*2022 · 398 citations*](https://md.research.elamur.ai/free/en/papers/guo-2022-longt5-efficient-text-text-transformer/)
353. [**DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction**Mohammadreza Pourreza, Davood Rafiei*2023 · 397 citations*](https://md.research.elamur.ai/free/en/papers/pourreza-2023-din-sql-decomposed-context-learning/)
354. [**A Unified Generative Framework for Aspect-based Sentiment Analysis**Hang Yan, Junqi Dai, Tuo Ji, et al.*2021 · 396 citations*](https://md.research.elamur.ai/free/en/papers/yan-2021-unified-generative-framework-aspect-based/)
355. [**TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance**Fengbin Zhu, Wenqiang Lei, Youcheng Huang, et al.*2021 · 396 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2021-tat-qa-question-answering-benchmark/)
356. [**Long Range Arena: A Benchmark for Efficient Transformers**Yi Tay, Mostafa Dehghani, Samira Abnar, et al.*2020 · 396 citations*](https://md.research.elamur.ai/free/en/papers/tay-2020-long-range-arena-benchmark-efficient/)
357. [**A Challenge Dataset and Effective Models for Aspect-Based Sentiment Analysis**Qingnan Jiang, Lei Chen, Ruifeng Xu, et al.*2019 · 393 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2019-challenge-dataset-effective-models-aspect/)
358. [**A Unified Generative Framework for Various NER Subtasks**Hang Yan, Tao Gui, Junqi Dai, et al.*2021 · 392 citations*](https://md.research.elamur.ai/free/en/papers/yan-2021-unified-generative-framework-various-ner/)
359. [**Cross-lingual Transfer Learning for Multilingual Task Oriented Dialog**Sebastian Schuster, Sonal Gupta, Rushin Shah, et al.*2019 · 390 citations*](https://md.research.elamur.ai/free/en/papers/schuster-2019-cross-lingual-transfer-learning-multilingual/)
360. [**BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models**Elad Ben-Zaken, Shauli Ravfogel, Yoav Goldberg*2021 · 388 citations*](https://md.research.elamur.ai/free/en/papers/ben-zaken-2021-bitfit-simple-parameter-efficient-fine/)
361. [**Combating Adversarial Misspellings with Robust Word Recognition**Danish Pruthi, Bhuwan Dhingra, Zachary C. Lipton*2019 · 388 citations*](https://md.research.elamur.ai/free/en/papers/pruthi-2019-combating-adversarial-misspellings-robust-word/)
362. [**WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents**Shunyu Yao, Howard Chen, John Yang, et al.*2022 · 387 citations*](https://md.research.elamur.ai/free/en/papers/yao-2022-webshop-towards-scalable-real-world/)
363. [**Representation Engineering: A Top-Down Approach to AI Transparency**Andy Zou, Long Phan, Sarah Chen, et al.*2023 · 386 citations*](https://md.research.elamur.ai/free/en/papers/zou-2023-representation-engineering-top-down-approach/)
364. [**German's Next Language Model**Branden Chan, Stefan Schweter, Timo Möller*2020 · 385 citations*](https://md.research.elamur.ai/free/en/papers/chan-2020-german-s-next-language-model/)
365. [**Tangled up in BLEU: Reevaluating the Evaluation of Automatic Machine Translation Evaluation Metrics**Nitika Mathur, Timothy Baldwin, Trevor Cohn*2020 · 385 citations*](https://md.research.elamur.ai/free/en/papers/mathur-2020-tangled-up-bleu-reevaluating-evaluation/)
366. [**Pooled Contextualized Embeddings for Named Entity Recognition**Alan Akbik, Tanja Bergmann, Roland Vollgraf*2019 · 385 citations*](https://md.research.elamur.ai/free/en/papers/akbik-2019-pooled-contextualized-embeddings-named-entity/)
367. [**A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding**Libo Qin, Wanxiang Che, Yangming Li, et al.*2019 · 384 citations*](https://md.research.elamur.ai/free/en/papers/qin-2019-stack-propagation-framework-token-level/)
368. [**Query Rewriting in Retrieval-Augmented Large Language Models**Xinbei Ma, Yeyun Gong, Pengcheng He, et al.*2023 · 383 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-query-rewriting-retrieval-augmented-large/)
369. [**Retrieval Augmentation Reduces Hallucination in Conversation**Kurt Shuster, Spencer Poff, Moya Chen, et al.*2021 · 382 citations*](https://md.research.elamur.ai/free/en/papers/shuster-2021-retrieval-augmentation-reduces-hallucination-conversation/)
370. [**Aligning AI With Shared Human Values**Dan Hendrycks, Collin Burns, Steven Basart, et al.*2020 · 382 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2020-aligning-ai-shared-human-values/)
371. [**Discourse-Aware Neural Extractive Text Summarization**Jiacheng Xu, Zhe Gan, Yu Cheng, et al.*2019 · 382 citations*](https://md.research.elamur.ai/free/en/papers/xu-2019-discourse-aware-neural-extractive-text/)
372. [**PyTorch Distributed: Experiences on Accelerating Data Parallel Training**Shen Li, Yanli Zhao, Rohan Varma, et al.*2020 · 380 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-pytorch-distributed-experiences-accelerating-data/)
373. [**UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training**Hangbo Bao, Li Dong, Furu Wei, et al.*2020 · 380 citations*](https://md.research.elamur.ai/free/en/papers/bao-2020-unilmv2-pseudo-masked-language-models/)
374. [**LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models**Neel Guha; Julian Nyarko; Daniel E. Ho; Christopher Re; Adam Chilton; Aditya Narayana; Alex Chohlas-Wood; Austin Peters; Brandon Waldon; Daniel N. Rockmore; Diego Zambrano; Dmitry Talisman; Enam Hoque; Faiz Surani; Frank Fagan; Galit Sarfaty; Gregory M. Dickinson; Haggai Porat; Jason Hegland; Jessica Wu; Joe Nudell; Joel Niklaus; John Nay; Jonathan H. Choi; Kevin Tobia; Margaret Hagan; Megan Ma; Michael Livermore; Nikon Rasumov-Rahe; Nils Holzenberger; Noam Kolt; Peter Henderson; Sean Rehaag; Sharad Goel; Shang Gao; Spencer Williams; Sunny Gandhi; Tom Zur; Varun Iyer;, Zehua Li*2023 · 379 citations*](https://md.research.elamur.ai/free/en/papers/guha-2023-legalbench-collaboratively-built-benchmark-measuring/)
375. [**Reasoning with Latent Structure Refinement for Document-Level Relation Extraction**Guoshun Nan, Zhijiang Guo, Ivan Sekulic, et al.*2020 · 379 citations*](https://md.research.elamur.ai/free/en/papers/nan-2020-reasoning-latent-structure-refinement-document/)
376. [**Fine-Grained Analysis of Propaganda in News Articles**Giovanni Da San Martino, Seunghak Yu, Alberto Barrón-Cedeño, et al.*2019 · 379 citations*](https://md.research.elamur.ai/free/en/papers/martino-2019-fine-grained-analysis-propaganda-news/)
377. [**Open Sesame: Getting inside BERT's Linguistic Knowledge**Yongjie Lin, Yi Chern Tan, Robert Frank*2019 · 379 citations*](https://md.research.elamur.ai/free/en/papers/lin-2019-open-sesame-getting-inside-bert/)
378. [**Towards General Text Embeddings with Multi-stage Contrastive Learning**Zehan Li, Xin Zhang, Yanzhao Zhang, et al.*2023 · 378 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-towards-general-text-embeddings-multi/)
379. [**Emerging Cross-lingual Structure in Pretrained Language Models**Alexis Conneau, Shijie Wu, Haoran Li, et al.*2020 · 378 citations*](https://md.research.elamur.ai/free/en/papers/conneau-2020-emerging-cross-lingual-structure-pretrained/)
380. [**ETC: Encoding Long and Structured Inputs in Transformers**Joshua Ainslie, Santiago Ontañón, Chris Alberti, et al.*2020 · 377 citations*](https://md.research.elamur.ai/free/en/papers/ainslie-2020-etc-encoding-long-structured-inputs/)
381. [**Tool Learning with Foundation Models**Yujia Qin, Shengding Hu, Yankai Lin, et al.*2023 · 376 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-tool-learning-foundation-models/)
382. [**HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data**Wenhu Chen, Hanwen Zha, Zhiyu Chen, et al.*2020 · 376 citations*](https://md.research.elamur.ai/free/en/papers/chen-2020-hybridqa-dataset-multi-hop-question/)
383. [**Editing Models with Task Arithmetic**Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.*2022 · 374 citations*](https://md.research.elamur.ai/free/en/papers/ilharco-2022-editing-models-task-arithmetic/)
384. [**FastBERT: a Self-distilling BERT with Adaptive Inference Time**Weijie Liu, Peng Zhou, Zhiruo Wang, et al.*2020 · 374 citations*](https://md.research.elamur.ai/free/en/papers/liu-2020-fastbert-self-distilling-bert-adaptive/)
385. [**A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers**Pradeep Dasigi, Kyle Lo, Iz Beltagy, et al.*2021 · 372 citations*](https://md.research.elamur.ai/free/en/papers/dasigi-2021-dataset-information-seeking-questions-answers/)
386. [**Position-Aware Tagging for Aspect Sentiment Triplet Extraction**Lu Xu, Hao Li, Wei Lu, et al.*2020 · 370 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-position-aware-tagging-aspect-sentiment/)
387. [**Green AI**Roy Schwartz, Jesse Dodge, Noah A. Smith, et al.*2019 · 370 citations*](https://md.research.elamur.ai/free/en/papers/schwartz-2019-green-ai/)
388. [**Invariant Risk Minimization**Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, et al.*2019 · 370 citations*](https://md.research.elamur.ai/free/en/papers/arjovsky-2019-invariant-risk-minimization/)
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